Utilization of smoking cessation informational, interactive, and online community resources as predictors of abstinence: cohort study.
Utilization of smoking cessation informational, interactive, and online community resources as predictors of abstinence: cohort study.
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DOI：
10.2196/jmir.1018
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发表时间：
2008-12-20
影响因子：
7.4
通讯作者：
Luxenberg MG
中科院分区：
文献类型：
--
作者：
An LC;Schillo BA;Saul JE;Wendling AH;Klatt CM;Berg CJ;Ahulwalia JS;Kavanaugh AM;Christenson M;Luxenberg MG
人们普遍认识到更多地利用网络辅助烟草干预措施与戒烟率增加之间的联系。然而，关于特定网站功能的使用如何影响戒烟的信息很少。 为了确定信息，互动和在线社区资源（如）的利用之间的关联。电子公告板）和戒烟率，更广泛的目标是确定改善网络辅助烟草干预成果的潜在战略。 2004年春，607名quitplan.com用户同意参与quitplan.com的评估，这是明尼苏达州的QuitNet.com品牌版本。我们开发了不同的网站功能的利用措施：一般信息，交互式诊断工具和退出规划工具，在线专家咨询，被动（即，阅读的公告板）和主动（即，公开张贴）在线社区参与，一对一的消息与其他虚拟社区成员。使用双变量、多变量和路径分析，我们检查了特定部位特征的利用与6个月时30天禁欲之间的关系。 最常用的资源是交互式戒烟计划工具（77%的网站用户使用）。其他信息资源（如戒烟指南）比被动（38%）或主动（24%）社区功能更常用（60%）。通过一对一消息传递的在线社区参与度很低（11%），使用在线咨询（5%）也很低。研究参与者在6个月时的30天戒烟率为9.7%（95%置信区间[CI] 7.3% - 12.1%）。在logistic回归模型中，人口统计学数据（例如，年龄，性别，教育水平，就业或保险状况）或吸烟相关数据（例如，每日吸烟量，第一支早晨吸烟的时间，基线戒烟准备）或戒烟药物的使用均未进入模型作为戒烟的重要预测因素。使用交互式戒烟计划工具一次、两到三次或四次或更多次的个体的戒烟几率分别为0.65（95%置信区间[CI] 0.22 - 1.94）、1.87（95% CI 0.77 - 4.56）和2.35（95% CI 1.0 - 5.58）。一对一消息的使用（参考=无vs 1或更多）进入最终模型作为禁欲的潜在预测因素，尽管该指标的显着性很小（OR = 1.91，95%CI 0.92 - 3.97，P = 0.083）。在路径分析中，活跃的在线社区参与和禁欲之间的明显关联在很大程度上是由于交互式戒烟工具和一对一消息传递的使用增加。 使用交互式戒烟工具，也许是与在线社区的其他成员一对一的消息传递，与quitplan.com用户的戒烟率增加有关。应考虑便于使用这些功能的设计。
The association between greater utilization of Web-assisted tobacco interventions and increased abstinence rates is well recognized. However, there is little information on how utilization of specific website features influences quitting. To determine the association between utilization of informational, interactive, and online community resources (eg. bulletin boards) and abstinence rates, with the broader objective to identify potential strategies for improving outcomes for Web-assisted tobacco interventions. In Spring 2004, a cohort of 607 quitplan.com users consented to participate in an evaluation of quitplan.com, a Minnesota branded version of QuitNet.com. We developed utilization measures for different site features: general information, interactive diagnostic tools and quit planning tools, online expert counseling, passive (ie, reading of bulletin boards) and active (ie, public posting) online community engagement, and one-to-one messaging with other virtual community members. Using bivariate, multivariate, and path analyses, we examined the relationship between utilization of specific site features and 30-day abstinence at 6 months. The most commonly used resources were the interactive quit planning tools (used by 77% of site users). Other informational resources (ie, quitting guides) were used more commonly (60% of users) than passive (38%) or active (24%) community features. Online community engagement through one-to-one messaging was low (11%) as was use of online counseling (5%). The 30-day abstinence rate among study participants at 6 months was 9.7% (95% Confidence Interval [CI] 7.3% - 12.1%). In the logistic regression model, neither the demographic data (eg, age, gender, education level, employment, or insurance status) nor the smoking-related data (eg, cigarettes per day, time to first morning cigarette, baseline readiness to quit) nor use of smoking cessation medications entered the model as significant predictors of abstinence. Individuals who used the interactive quit planning tools once, two to three times, or four or more times had an odds of abstinence of 0.65 (95% Confidence Interval [CI] 0.22 - 1.94), 1.87 (95% CI 0.77 - 4.56), and 2.35 (95% CI 1.0 - 5.58), respectively. The use of one-to-one messages (reference = none vs 1 or more) entered the final model as potential predictor for abstinence, though the significance of this measure was marginal (OR = 1.91, 95% CI 0.92 - 3.97, P = .083). In the path analysis, an apparent association between active online community engagement and abstinence was accounted for in large part by increased use of interactive quitting tools and one-to-one messaging. Use of interactive quitting tools, and perhaps one-to-one messaging with other members of the online community, was associated with increased abstinence rates among quitplan.com users. Designs that facilitate use of these features should be considered.
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影响因子：
12.7
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全州基于互联网的烟草戒烟干预的影响。
影响因子：
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